Identifying key drivers of extinction for Chitala populations: data-driven insights from an intraguild predation model using a Bayesian framework

IF 3 4区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES Environmental and Ecological Statistics Pub Date : 2024-08-13 DOI:10.1007/s10651-024-00631-9
Dipali Vasudev Mestry, Md Aktar Ul Karim, Joyita Mukherjee, Amiya Ranjan Bhowmick
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Abstract

The fish species N. chitala is a freshwater fish that is widely distributed in African and Asian countries, including India, Pakistan, Bangladesh, Sri Lanka, Nepal, Thailand, and Indonesia. This species has been categorized as endangered (EN) in the Conservation Assessment and Management Plan. The study aims to investigate the cause of the species’ decline in their natural habitat. Using mathematical models supported by empirical data analysis, we explore the interaction of the species with other tropic levels and discover important parameters that may be attributed to the rapid decline. Based on the literature, we considered an intraguild predation (IGP) system consisting of three species, namely Chitala (IG predator), Mugil (IG prey), and shrimp (resource). Two variants of IGP models governed by three coupled differential equations are considered for data modeling purposes. Chitala depends only on Mugil and shrimp in one model. An alternative food source is available to Chitala in the second model. The models are estimated using the Bayesian modeling framework. Posterior estimates of the parameters for each model were obtained using the Gibbs algorithm, and the reversible-jump Markov chain Monte Carlo method has been utilized for posterior model inference. Our findings suggest that the primary reason for the decline in Chitala is due to the reduced nutritional gain from the Mugil and reduced predation efficiency in acquiring shrimp as a food source in the unavailability of Mugil. This study may be useful to develop management strategies for Chitala conservation by emphasizing the regeneration of Mugil populations.

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确定导致奇塔拉种群灭绝的关键因素:利用贝叶斯框架从野兽内部捕食模型中获得的数据驱动见解
奇塔拉鱼(N. chitala)是一种淡水鱼,广泛分布于非洲和亚洲国家,包括印度、巴基斯坦、孟加拉国、斯里兰卡、尼泊尔、泰国和印度尼西亚。该物种在《保护评估和管理计划》中被列为濒危物种(EN)。本研究旨在调查该物种在其自然栖息地减少的原因。利用经验数据分析支持下的数学模型,我们探索了该物种与其他热带水平的相互作用,并发现了可能导致其迅速衰退的重要参数。根据文献,我们考虑了一个由三个物种组成的群体内捕食(IGP)系统,即 Chitala(IG 捕食者)、Mugil(IG 猎物)和虾(资源)。为了建立数据模型,我们考虑了由三个耦合微分方程控制的两种 IGP 模型变体。在一个模型中,Chitala 只依赖 Mugil 和虾。在第二个模型中,Chitala 可以获得另一种食物来源。这些模型采用贝叶斯建模框架进行估计。每个模型参数的后验估计值都是用吉布斯算法获得的,后验模型推断采用了可逆跳跃马尔科夫链蒙特卡罗方法。我们的研究结果表明,Chitala减少的主要原因是Mugil的营养增益减少,以及在Mugil不存在的情况下捕食虾作为食物来源的效率降低。这项研究可能有助于通过强调鲻鱼种群的再生来制定保护赤塔鱼的管理策略。
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来源期刊
Environmental and Ecological Statistics
Environmental and Ecological Statistics 环境科学-环境科学
CiteScore
5.90
自引率
2.60%
发文量
27
审稿时长
>36 weeks
期刊介绍: Environmental and Ecological Statistics publishes papers on practical applications of statistics and related quantitative methods to environmental science addressing contemporary issues. Emphasis is on applied mathematical statistics, statistical methodology, and data interpretation and improvement for future use, with a view to advance statistics for environment, ecology and environmental health, and to advance environmental theory and practice using valid statistics. Besides clarity of exposition, a single most important criterion for publication is the appropriateness of the statistical method to the particular environmental problem. The Journal covers all aspects of the collection, analysis, presentation and interpretation of environmental data for research, policy and regulation. The Journal is cross-disciplinary within the context of contemporary environmental issues and the associated statistical tools, concepts and methods. The Journal broadly covers theory and methods, case studies and applications, environmental change and statistical ecology, environmental health statistics and stochastics, and related areas. Special features include invited discussion papers; research communications; technical notes and consultation corner; mini-reviews; letters to the Editor; news, views and announcements; hardware and software reviews; data management etc.
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